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DOE OSTI2016

The sloan digital sky survey reverberation mapping project: velocity shifts of quasar emission lines

Quasar emission lines are often shifted from the systemic velocity due to various dynamical and radiative processes in the line-emitting region. The level of these velocity shifts depends both on the line species and on quasar properties. We study velocity shifts for the line peaks (not the centroids) of various narrow and broad quasar emission lines relative to systemic using a sample of 849 quasars from the Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project. The coadded (from 32 epochs) spectra of individual quasars have sufficient signal-to-noise ratio (S/N) to measure stellar absorption lines to provide reliable systemic velocity estimates, as well as weak narrow emission lines. The large dynamic range in quasar luminosity (∼2 dex) of the sample allowed us to explore potential luminosity dependence of the velocity shifts. We derive average line peak velocity shifts as a function of quasar luminosity for different lines, and quantify their intrinsic scatter. We further quantify how well the peak velocity can be measured as a function of continuum S/N, and demonstrate that there is no systematic bias in the velocity measurements when S/N is degraded to as low as ∼3 per SDSS pixel (∼69 km s{sup −1}). Based on the observed line shifts, we provide empirical guidelines on redshift estimation from [O ii] λ3727, [O iii] λ5007, [Ne v] λ3426, Mg ii, C iii], He ii λ1640, broad Hβ, C iv, and Si iv, which are calibrated to provide unbiased systemic redshifts in the mean, but with increasing intrinsic uncertainties of 46, 56, 119, 205, 233, 242, 400, 415, and 477 km s{sup −1}, in addition to the measurement uncertainties. These results demonstrate the infeasibility of measuring quasar redshifts to better than ∼200 km s{sup −1} with only broad lines.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Quantum phase-sensitive diffraction and imaging using entangled photons

We propose a quantum diffraction imaging technique whereby one photon of an entangled pair is diffracted off a sample and detected in coincidence with its twin. The image is obtained by scanning the photon that did not interact with matter. We show that when a dynamical quantum system interacts with an external field, the phase information is imprinted in the state of the field in a detectable way. The contribution to the signal from photons that interact with the sample scales as ∝ I p 1 / 2 , where I p is the source intensity, compared with ∝ I p of classical diffraction. This makes imaging with weak fields possible, providing high signal-to-noise ratio, avoiding damage to delicate samples. A Schmidt decomposition of the state of the field can be used for image enhancement by reweighting the Schmidt modes contributions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Dynamics of Shape-Persistent Giant Molecules: Zimm-like Melt, Elastic Plateau, and Cooperative Glass-like

Giant molecules are a new class of soft matter having threedimensional (3D) shapes and composed of chemically linked rigid molecular nanoparticles. Structurally, a 3D cluster of molecular nanoparticles can be one giant molecule or a few giant molecules associated together via specific interactions. The dynamics of clusters that are smaller than a critical diameter (~5 nm) presents a power law relaxation exponent of 0.7 at the high frequency region corresponding to segmental dynamics. Such scaling is similar to the result of the Zimm model although those clusters are neither chain-like nor in solution. Clusters that are larger than this critical diameter and formed by the association of giant molecules exhibit an elastic plateau due to caging of individual giant molecules. Herein, we hypothesize that clusters of such a large size cannot move as a whole, even above the glass transition temperature of the sample. They thus are “cooperative glass-like”. A structural cluster of giant molecules could be abstracted as a dynamical cluster consisting of unlinked but cooperatively mobile beads. As derived in the random first-order transition theory, the cluster loses its mobility and reaches the glassy state when the diameter of the cluster is 6 times larger than the bead diameter. In our cases, we estimate that the critical diameter for these clusters is also approximately 6 times the bead diameter based on the glassy shear modulus of giant molecules. Thus, shape-persistent giant molecules may serve as a bridge between polymers and colloids and a platform to mimic cooperative rearrangements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale

The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges.

NMDC, Microbiome↗

DOE OSTI2024

Dynamic Control of Sodium Cold Trap Purification Temperature Using LSTM System Identification

This study investigates the dynamic regulation of the sodium cold trap purification temperature at Argonne National Laboratory’s liquid sodium test facility, employing long short-term memory (LSTM) system identification techniques. The investigation introduces an innovative hybrid approach by integrating model predictive control (MPC) based on first principles dynamic models with a multi-step time–frequency LSTM model in predicting the temperature profiles of a sodium cold trap purification system. The long short-term memory–model predictive controller (LSTM-MPC) model employs a sliding window scheme to gather training samples for multi-step prediction, leveraging historical data to construct predictive models that capture the non-linearities of the complex system dynamics without explicitly modeling the underlying physical processes. The performance of the LSTM-MPC and MPC were evaluated through simulation experiments, where both models were assessed on their capacity to maintain the cold trap temperature within predefined set-points while minimizing deviations and overshoots. Results obtained show how the data-driven LSTM-MPC model demonstrates stability and adaptability. In contrast, the traditional MPC model exhibits irregularities, particularly evident as overshoots around set-point limits, which can potentially compromise its effectiveness over long prediction time intervals. The findings obtained offer valuable insights into integrating data-driven techniques for enhancing real-time monitoring systems.

LSTM-MPC↗

DOE OSTI2022

The estimation of Poisson’s ratio by time-averaging and Cornu’s method for isotropic beams

Prior research suggests that direct static (e.g., uniaxial testing) and dynamic (e.g., ultrasonic wave propagation analysis) measurements differ in the estimation of Poisson’s ratio because anisotropies and heterogeneities in the sample material affect the two types of tests differently. Even assuming isotropic and homogeneous material properties, prior research further suggests that discrepancies between static/dynamic test results will exist because the error of the diagnostic techniques for the measurand are inherently different. Finally, thermodynamic effects are not present in static tests but can significantly affect dynamic test results. Given the potential for all these variables to produce discrepancies, it would be helpful to have the measurement of Poisson’s ratio obtainable from the same theory and experimental measurements by either static or dynamic testing methods. Our finite element calculations show that by combining time-averaged scanning digital holography with Cornu’s method, it is theoretically possible to estimate the effective Poisson’s ratio from the anticlastic contours at the antinode of the first out-of-plane bending mode shape. This is true regardless of frequency and therefore applicable for both static and dynamic measurements. Our results show that the estimate of Poisson’s ratio by Cornu’s method using data from simulations of mode shapes approaches the true value of Poisson’s ratio. Additionally, our research suggests that beam geometry and boundary conditions are fundamental factors limiting the convergence of the estimate of Poisson’s ratio to the true value of Poisson’s ratio regardless of performing a static or dynamic test.

42 ENGINEERING↗

DOE OSTI2024

Asymmetric drift in MaNGA: mass and radially dependent stratification rates in galaxy discs

ABSTRACT We measure the age–velocity relationship from the lag between ionized gas and stellar tangential speeds in ∼500 nearby disc galaxies from MaNGA in Sloan Digital Sky Survey IV (SDSS-IV). Selected galaxies are kinematically axisymmetric. Velocity lags are asymmetric drift, seen in the Milky Way’s (MW) solar neighbourhood and other Local Group galaxies; their amplitude correlates with stellar population age. The trend is qualitatively consistent in rate ($\dot{\sigma }$) with a simple power-law model where σ ∝ tb that explains the dynamical phase-space stratification in the solar neighbourhood. The model is generalized based on disc dynamical times to other radii and other galaxies. We find in-plane radial stratification parameters σ0,r (dispersion of the youngest populations) in the range of 10–40 km s−1 and 0.2 < br < 0.5 for MaNGA galaxies. Overall, brincreases with galaxy mass, decreases with radius for galaxies above 10.4 dex (M⊙) in stellar mass, but is ∼constant with radius at lower mass. The measurement scatter indicates the stratification model is too simple to capture the complexity seen in the data, unsurprising given the many possible astrophysical processes that may lead to stellar population dynamical stratification. None the less, the data show dynamical stratification is broadly present in the galaxy population, with systematic trends in mass and density. The amplitude of the asymmetric drift signal is larger for the MaNGA sample than the MW, and better represented in the mean by what is observed in the discs of M31 and M33. Either typical discs have higher surface-density or, more likely, are dynamically hotter (hence thicker) than the MW.

Bershady, Matthew A. (ORCID:0000000231314374)↗

DOE OSTI2019

Protein and RNA dynamical fingerprinting

Protein structural vibrations impact biology by steering the structure to functional intermediate states; enhancing tunneling events; and optimizing energy transfer. Strong water absorption and a broad continuous vibrational density of states have prevented optical identification of these vibrations. Recently spectroscopic signatures that change with functional state were measured using anisotropic terahertz microscopy. The technique however has complex sample positioning requirements and long measurement times, limiting access for the biomolecular community. Here we demonstrate that a simplified system increases spectroscopic structure to dynamically fingerprint biomacromolecules with a factor of 6 reduction in data acquisition time. Using this technique, polarization varying anisotropy terahertz microscopy, we show sensitivity to inhibitor binding and unique vibrational spectra for several proteins and an RNA G-quadruplex. The technique’s sensitivity to anisotropic absorbance and birefringence provides rapid assessment of macromolecular dynamics that impact biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Exploring Bioeconomy Growth through the Public Release of the Biomass Scenario Model

The Biomass Scenario Model (BSM) is an important tool for exploring vibrant future bioeconomy scenarios that leverage domestic resources. Developed by NREL and BETO, this model of the domestic biofuels supply chain has been used to explore success strategies for BETO's activities towards bioeconomy growth. The BSM offers a robust test bed for detailed exploration of effects of BETO activities within the complex context of resource availability; physical, technological, and economic constraints; behavior; and policy. The public release of the model in 2017 will allow broad engagement with the theme of the conference as model users can analyze bioeconomy growth, domestic biomass resource use, and associated effects. The BSM is a carefully validated, state-of-the-art, dynamic model of the biomass to biofuels supply chain. Using a system dynamics simulation modeling approach, the model tracks long-term deployment of biofuels given technology development and investment, considering land availability, the competing oil market, consumer demand, and government policies over time. Sample outputs include biofuels production, feedstock use, capital investment, incentives, and costs of feedstocks and fuels. BSM scenarios reveal technological, economic, and policy challenges, as well as opportunities for dynamic growth of the bioeconomy with strategic public and private investment at key points in the system. The model logic and results have been reviewed extensively, through collaborative analysis, expert reviews and external publications (https://www.zotero.org/groups/bsm_publications/).

09 BIOMASS FUELS↗

DOE OSTI2025

Rheological Properties of Enzymatically Hydrolyzed Corn Stover Pretreated via Deacetylation and Mechanical Refining

Lignocellulosic biomass is a feedstock for fuels and chemicals that does not compete with food resources and has less contaminants than refuse-derived biomass feedstocks. To convert lignocellulosics to biofuels or value-added products, multiple processing steps are typically necessary. One method of producing biofuels from lignocellulosic biomass utilizes a deacetylation and mechanical refining pretreatment and an enzymatic hydrolysis reaction to produce fermentable sugars from cellulose and hemicellulose. The rheological properties of biomass, such as yield stress and plastic viscosity, change during enzymatic hydrolysis and alter the energy requirements for pumping and mixing, an important consideration for the design of processing equipment. The dynamic changes in rheological properties that occur in a corn stover feedstock undergoing enzymatic hydrolysis are characterized in this work, and the influence on pressure losses in piping systems is estimated. Two rheometer geometries were fabricated with stereolithography 3D printing to reduce wall slip and sample ejection. The slurries have complex rheological behaviors that include shear-thinning behavior. Shear stress ramps were performed on samples at 20 and 50 degrees C using the custom geometries, and the Herschel-Bulkley model was fit to the data. The dynamic nature of the rheological properties is correlated with changes in the average fiber length at various extents of reaction, and the influence of solids concentration on the observed rheology and piping pressure losses is discussed.

09 BIOMASS FUELS↗

DOE OSTI2024

Factors Predicting Apparent Ophidiomycosis in Wild Brown Watersnakes ( Nerodia Taxispilota )

Ophidiomycosis, also known as snake fungal disease, is caused by Ophidiomyces ophidiicola and is a threat to snake conservation worldwide. Ophidiomycosis has been reported throughout much of the eastern US, and outbreaks have been associated with local population declines of already strained populations. Previous studies report significant variability in ophidiomycosis among species sampled, with higher prevalence typically observed in Nerodia spp. Although ophidiomycosis can lead to morbidity and mortality in affected individuals, little is known about disease dynamics in free-ranging populations. Herein, we examine how individual-specific factors (e.g., life stage [immature, mature], contaminant status, sex, hemograms) may be associated with ophidiomycosis status in the brown watersnake (Nerodia taxispilota). During 2018–19, we sampled 97 N. taxispilota from five locations along the Savannah River in South Carolina and Georgia, US. Ophidiomyces ophidiicola DNA was detected in 66 snakes for a prevalence of 68% (95% confidence interval, 59–77). Mature snakes had a significantly higher risk of apparent ophidiomycosis (skin lesions present and quantitative PCR [qPCR], positive) relative to immature snakes. Snakes classified as having possible (skin lesions present, but qPCR negative) or apparent ophidiomycosis exhibited a relative azurophilia and heterophilia compared with individuals classified as negative (P≤0.037). Nerodia taxispilota in this region appear to have a high prevalence of apparent ophidiomycosis (22%; 95% CI, 14–31), similar to previous reports from the southeastern US. Furthermore, additional epidemiologic investigations are warranted to further elucidate other individual-specific and environmental factors that may dictate disease risk and outcomes in affected populations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Ultrashort XUV pulse absorption spectroscopy of partially oxidized cobalt nanoparticles

High-order harmonic generation (HHG) based transient extreme ultraviolet (XUV) absorption spectroscopy is an emerging technique to trace photoinduced charge carrier dynamics in condensed phase materials with femtosecond and even attosecond temporal resolution and elemental specificity. However, its application to nanoparticulate samples that are relevant, for example, for novel photocatalytic light harvesting concepts, has been limited. This is in part due to the challenge to produce residual-free samples on ultrathin, XUV-transparent substrates as well as a widespread understanding that sparsely distributed nanoparticles do not provide sufficient contrast for XUV absorption measurements. Here, we present static XUV absorption spectra of partially oxidized Co nanowire-structures with diameters of approximately 4.5 nm and lengths between 10 and 40 nm, recorded with an ultrashort pulse HHG light source. Nanoparticles are synthesized by the agglomeration of Co atoms inside superfluid helium droplets, followed by surface deposition and oxidation in ambient air. The method is uniquely suited for residual-free synthesis of transition metal nanowires and their deposition on ultrathin substrates. Analysis by high-resolution transmission electron microscopy reveals the formation of CoO nanowires with regions of unoxidized Co in their interior. The nanoparticle samples are investigated in an HHG-driven ultrafast XUV absorption setup. Despite the low surface coverage of only 23%, the recorded spectrum exhibits a distinct absorption feature at the Co M 2,3 (2p) edge near 60 eV with a peak height of about 40 mOD. Finally, the results support the feasibility of table-top ultrafast transient XUV absorption studies of photoinduced dynamics in transition metal oxide nanoparticles with sub-monolayer surface coverage.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2016

Molecular structure of vapor-deposited amorphous selenium

The structure of amorphous selenium is clouded with much uncertainty and contradictory results regarding the dominance of polymeric chains versus monomer rings. The analysis of the diffraction radial distribution functions are inconclusive because of the similarities between the crystalline allotropes of selenium in terms of the coordination number, bond length, bond angle, and dihedral angle. Here, we took a much different approach and probed the molecular symmetry of the thermodynamically unstable amorphous state via analysis of structural phase transformations. We verified the structure of the converted metastable and stable crystalline structures using scanning transmission electron microscopy. In addition, given that no experimental technique can tell us the exact three-dimensional atomic arrangements in glassy semiconductors, we performed molecular-dynamic simulations using a well-established empirical three-body interatomic potential. In this work, we developed a true vapor-deposited process for the deposition of selenium molecules onto a substrate using empirical molecular vapor compositions and densities. We prepared both vapor-deposited and melt-quenched samples and showed that the simulated radial distribution functions match very well to experiment. The combination of our experimental and molecular-dynamic analyses shows that the structures of vapor- and melt-quenched glassy/amorphous selenium are quite different, based primarily on rings and chains, respectively, reflecting the predominant structure of the parent phase in its thermodynamic equilibrium.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Data Analysis Approaches for the Risk-Informed Safety Margins Characterization Toolkit

In the past decades, several numerical simulation codes have been employed to simulate accident dynamics (e.g., RELAP5-3D, RELAP-7, MELCOR, MAAP). In order to evaluate the impact of uncertainties into accident dynamics, several stochastic methodologies have been coupled with these codes. These stochastic methods range from classical Monte-Carlo and Latin Hypercube sampling to stochastic polynomial methods. Similar approaches have been introduced into the risk and safety community where stochastic methods (such as RAVEN, ADAPT, MCDET, ADS) have been coupled with safety analysis codes in order to evaluate the safety impact of timing and sequencing of events. These approaches are usually called Dynamic PRA or simulation-based PRA methods. These uncertainties and safety methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). The scope of this paper is to present a broad overview of methods and algorithms that can be used to analyze and extract information from large data sets containing time dependent data. In this context, “extracting information” means constructing input-output correlations, finding commonalities, and identifying outliers. Some of the algorithms presented here have been developed or are under development within the RAVEN statistical framework.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1984

Sampling strategies and four-dimensional assimilation of altimetric data for ocean monitoring and prediction

Numerical experiments using simulated altimeter data were conducted in order to examine the assimilation of altimeter-derived sea surface heights into numerical ocean circulation models. A reduced-gravity, primitive equation circulation model of the Gulf of Mexico was utilized; the Gulf of Mexico was chosen because of its amenability to modeling and the ability of low vertical-mode models to reproduce the observed dynamical features of the Gulf circulation. The simulated data were obtained by flying an imaginary altimeter over the model ocean and sampling the model sea surface just as real altimeter would observe the true ocean. The data were used to initialize the numerical model and the subsequent forecast was compared to the true numerical solution. Results indicate that for a stationary, circular eddy, approximately three to four tracks (either ascending or descending) across the eddy are sufficient to ensure adequate spatial resolution.

Kindle, J. C.↗

DOE OSTI2019

Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice

Large-scale phosphoproteomics with coverage of over 10,000 sites of phosphorylation have now been routinely achieved with advanced mass spectrometry (MS)-based workflows. However, accurate targeted MS-based quantification of phosphorylation dynamics, an important direction for gaining quantitative understanding of signaling pathways or networks, has been much less investigated. Herein, we report an assessment of the targeted workflow in the context of signal transduction pathways, using the epidermal growth factor receptor (EGFR)–mitogen-activated protein kinase (MAPK) pathway as our model. 43 phosphopeptides from the EGFR–MAPK pathway were selected for the study. The recovery and sensitivity of a workflow consisted of two commonly used enrichment methods, immobilized metal affinity chromatography (IMAC) and titanium oxide (TiO2), combined with selected reaction monitoring (SRM)-MS, were evaluated. The recovery of phosphopeptides by IMAC and TiO2 enrichment was quantified to be 38 ± 5% and 58 ± 20%, respectively, based on internal standards. Moreover, both enrichment methods provided comparable sensitivity from 1-100 g starting peptides. Robust quantification was consistently achieved for most targeted phosphopeptides when starting with 25-100 g peptides. However, the numbers of quantified targets significantly dropped when peptide samples were in the 1-25g range. Finally, IMAC-SRM was applied to quantify signaling dynamics of EGFR-MAPK pathway in Hs578T cells following 3 ng/mL EGF treatment. The kinetics of phosphorylation clearly revealed early and late phases of phosphorylation, even for very low abundance proteins. These results demonstrate the feasibility of robust targeted quantification of phosphorylation dynamics for specific pathways, even starting with relatively small amounts of protein.

Sharon, Gil↗

DOE OSTI2018

Targeted Quantification of Phosphorylation Dynamics in the Context of EGFR-MAPK Pathway

Environmental Molecular Sciences Laboratory↗

DOE OSTI2017

Small Angle Neutron Scattering Studies of R67 Dihydrofolate Reductase, a Tetrameric Protein with Intrinsically Disordered N-Termini

R67 dihydrofolate reductase (DHFR) is a homotetramer with a single active site pore and no sequence or structural homology with chromosomal DHFRs. The R67 enzyme provides resistance to trimethoprim, an active site-directed inhibitor of Escherichia coli DHFR. Sixteen to twenty N-terminal amino acids are intrinsically disordered in the R67 dimer crystal structure. Chymotrypsin cleavage of 16 N-terminal residues results in an active enzyme with a decreased stability. We investigated the space sampled by the disordered N-termini of R67 DHFR using small angle neutron scattering. From a combined analysis using molecular dynamics and the program SASSIE (http://www.smallangles.net/sassie/SASSIE_HOME.html), the apoenzyme displays a radius of gyration (Rg) of 21.46 ± 0.50 Å. Addition of glycine betaine, an osmolyte, does not result in folding of the termini as the Rg increases slightly to 22.78 ± 0.87 Å. SASSIE fits of the latter SANS data indicate that the disordered N-termini sample larger regions of space and remain disordered, suggesting they might function as entropic bristles. Pressure perturbation calorimetry also indicated that the volume of R67 DHFR increases upon addition of 10% betaine and decreased at 20% betaine because of the dehydration of the protein. Studies of the hydration of full-length R67 DHFR in the presence of the osmolytes betaine and dimethyl sulfoxide find around 1250 water molecules hydrating the protein. Similar studies with truncated R67 DHFR yield around 400 water molecules hydrating the protein in the presence of betaine. The difference of ~900 waters indicates the N-termini are well-hydrated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗